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Programming for Engineers in Python

Programming for Engineers in Python. Lecture 13: Shit Happens. Autumn 2011-12. 1. Lecture 12: Highlights. Dynamic programming Overlapping subproblems Optimal structure Memoization Fibonacci Evaluating trader’s performance (maximum subarray sum) Optimizing shipping cargo (Knapsack). 2.

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Programming for Engineers in Python

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  1. Programming for Engineers in Python Lecture 13: Shit Happens Autumn 2011-12 1

  2. Lecture 12: Highlights • Dynamic programming • Overlapping subproblems • Optimal structure • Memoization • Fibonacci • Evaluating trader’s performance (maximum subarray sum) • Optimizing shipping cargo (Knapsack) 2

  3. Optimizing Shipping Cargo (Knapsack) • Shipping capacity W = 1000 • Offers from potential shippers n = 100 • Each offer i has a weight wi and an offered reward vi • Maximize the reward given the W tonnage limit • A(n,W) - the maximum value that can be attained from considering the first n items weighting at most W tons 3

  4. Solution (Recursive) 4

  5. Solution (Memoization) – The Idea M(N,W) W N 5

  6. Solution (Memoization) - Code 6

  7. Solution (Iterative) – The Idea In Class “Bottom-Up”: start with solving small problems and gradually grow M(N,W) W N 7

  8. DP: Iterative VS. Memoization • Same Big O computational complexity • If all subproblems must be solved at least once, iterative is better by a constant factor due to no recursive involvement • If some subproblems may not need to be solved, Memoized algorithm may be more efficient, since it only solve these subproblems which are definitely required

  9. Steps in Dynamic Programming • Characterize structure of an optimal solution • Define value of optimal solution recursively • Compute optimal solution values either top-down (memoization) or bottom-up (in a table) • Construct an optimal solution from computed values

  10. Why Knapsack? בעיית הגנב http://en.wikipedia.org/wiki/Knapsack_problem

  11. Extensions • NP completeness http://en.wikipedia.org/wiki/NP-complete • Pseudo polynomial http://en.wikipedia.org/wiki/Pseudo-polynomial_time

  12. Plan • (Quick overview on) Reading and writing files • (Quick overview on) Exceptions handling • Error correction / error detection • (Brief) Course summary • Python as a first language • HW, exams and exam tips 12

  13. IO in Python • This is NOT exam material • http://www.penzilla.net/tutorials/python/fileio/ • http://docs.python.org/tutorial/inputoutput.html#reading-and-writing-files 13

  14. Exceptions Handling in Python • This is NOT exam material • http://www.penzilla.net/tutorials/python/exceptions/ • http://docs.python.org/tutorial/errors.html#exceptions 14

  15. Magic Source: http://csu-il.blogspot.com/ 15

  16. Mind Reading Card Trick • Error correction / error identification • Error correcting for one card flip • What if 2 cards flip? 3? 4? • Applications: • Messages between computers • Hard disk drive • CD • Barcode • Spelling corraction 16

  17. Israeli ID Error Detection • Israeli ID: unique per person, 9 digits • Right most digit is control digit • How is the control checked? • Consider first 8 ID digits • For every 2nd digit d: • d < 5  write 2*d • d > 5  write 2*d + 1 – 10 (sum of 2*d digits) • The rest of the digits remain without change • ID 053326187 17

  18. Example: 053326187 0 5 3 3 2 6 1 8 7 + + + + + + + 0 1 3 6 2 3 1 7 = 23 (23 + control_digit) % 10 = 0 18

  19. Raid • Redundant array of independent disks • http://en.wikipedia.org/wiki/RAID • Add XOR disk • How to fix a flaw disk’s data? 19

  20. Course Summary Time travel to week #1 20

  21. Welcome! • You are about to take a new programming course in Python • This is the first run ever of this course • The idea is to enable you to use programming as a tool to solve “real world” problems • Hard work is required! 21

  22. Course Objectives Develop basic computing skills (programming, algorithms, applications) 22

  23. Practical Sessions • In a standard classroom • Purposes: • Practice topics that were presented in class • “Preparations” for next week’s class • Background for homework assignments • Learn practical tools • Lectures will be harder to understand, and it is ok… 23

  24. A Personal Note on HW • It will take you a lot of time and frustration • It is an engineering difficulty: figuring out what's wrong with a system and how to fix it • You're engineers: make it work! • There is no other way to learn how to program • Believe me… 24

  25. Syllabus Tentative, not in order, probably too ambitious • Python programming basics • Using packages • Recursion • Sort & search algorithms, runtime analysis • Dynamic programming • Error handling • Input/output • Graphical user interface (GUI) • Simulation • Optimization • Data analysis • Control • Signal processing 25

  26. My Motivation • What computational capabilities engineers “need”? • Be able to write simple scripts • Be able to use existing tools (modules) • Problems solving capabilities • Understand what and how CS people do • For better collaboration • General knowledge 26

  27. Python as a First Language • Based on Zelle’s paper from 1999http://mcsp.wartburg.edu/zelle/python/python-first.html • Popular alternatives: C, C++, Java • The advantages of using a scripting* language as a first language, specifically Python • * - Zelle’s words, never let someone tell you python isn't good because it's a scripting language (we’ll see why soon) 27

  28. Compiler (C, C++, Java (not exactly))

  29. Hello World (in C) ;-)

  30. Interpreter

  31. Criteria for a First Language • Requirements from a first programming course: • Learning how to program • Problem solving, design • Implications for Programming Language Choice • Simple syntax and semantics (simple problems should be solved simply) • Hands on: high level and flexible languages allow designs to be expressed with minimal overhead  encourages experimentation • Supports modern approaches to design and abstraction (e.g., OOP) • Widely available (not for “teaching only”, used in the “real world”) 31

  32. The Case for Scripting Languages • System programming languages (C, C++, Pascal, Java) • Statically typed • Usually compiled • Modest abstraction from the underlying machine • Scripting languages: • Dynamically typed • Usually interpreted • Very high level • Modern scripting languages are not “toy”/”glue” languages! • Pros • Very flexible encourage experimentation • Allow students to build more sophisticated and interesting projects with less implementation effort 32

  33. Python is Simple Python: C++: Java: 33

  34. Python has a Simple Uniform Data Model 34

  35. Python is Safe 35

  36. Python Supports OOP Stack as an example: 36

  37. Python is Fun • Simplicity makes it fun to learn • Data structures (dynamic array, hash table, immutable lists) and class mechanism can be used to quickly build • No type declarations  less code, more flexible • Huge libraries of modules • E.g., for GUI, client-server applications, html viewers, databases, animation • E.g., PIL, pygame, scipy, numpy, swampy, matplotlib,… 37

  38. Python is Practical • Scripting languages are gaining popularity. By some accounts, more software is written in scripting than system languages • Python is free • Python is a mature language • Widely industrial used (e.g., YouTube, BitTorrent, Google, Yahoo!, IDF, NASA), https://us.pycon.org/2012/sponsors/ 38

  39. Some Obstacles (Real and imagined) • Lack of compile time checking – next slide • Scripting languages are too inefficient • Python is unfamiliar (to lecturers…) • Our students want languages X • There aren’t any textbooks 39

  40. Lack of Compile Time Checking 40

  41. Lack of Compile Time Checking 41

  42. סקר שביעות רצון (הרשמי) 42

  43. Course’s HW • Total of 11 hw assignments • You must pass at least 7 assignments to be eligible to pass the course • HW will count for 20% of course’s grade • 10 highest assignments will count for the final grade

  44. Exam • One hand written double sided A4 page is allowed. Each student has to prepare his/her own page, photo-copying is not allowed • Two weeks before the exam we will publish sample questions in the spirit of the exam • A Q&A session will be held with the TAs a few days before the exam • Meanwhile, you can “feel” how it looks like by checking previous years exams (in C)

  45. Exam Tips • The exam material includes all that was taught in class, tirgul, and hw assignments. Yes, including today’s class • You can get 20% of each part by answering “I don’t know”  knowing that you do not know is much better than don’t knowing • I like to give questions that are highly similar to examples that were shown during the course • Read the questions carefully. Understanding what you are asked about is critical! 45

  46. Exam Tips • Question parts (סעיפים) are usually dependent. Most times you should use an earlier part when solving later parts in a given question. • You may (and should) solve a question part even if you have not solved previous parts • How to prepare? • Dealing with exam stress 46

  47. Good Luck! 47

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